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Gut commensal Christensenella minuta modulates host metabolism via acylated secondary bile acids

Nature Microbiology volume 9, pages 434–450 (2024)Cite this article

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Abstract

A strong correlation between gut microbes and host health has been observed in numerous gut metagenomic cohort studies. However, the underlying mechanisms governing host–microbe interactions in the gut remain largely unknown. Here we report that the gut commensal Christensenella minuta modulates host metabolism by generating a previously undescribed class of secondary bile acids with 3-O-acylation substitution that inhibit the intestinal farnesoid X receptor. Administration of C. minuta alleviated features of metabolic disease in high fat diet-induced obese mice associated with a significant increase in these acylated bile acids, which we refer to as 3-O-acyl-cholic acids. Specific knockout of intestinal farnesoid X receptor in mice counteracted the beneficial effects observed in their wild-type counterparts. Finally, we showed that 3-O-acyl-CAs were prevalent in healthy humans but significantly depleted in patients with type 2 diabetes. Our findings indicate a role for C. minuta and acylated bile acids in metabolic diseases.

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Fig. 1: Gut microbe-mediated biotransformation of CAs into previously unknown 3-O-acyl-CAs.
Fig. 2: The effects of C. minuta on the host metabolism in DIO mice.
Fig. 3: The effects of C. minuta on the intestinal FXR–enterohepatic signalling axis in DIO mice.
Fig. 4: The cell culture-based identification of the physiological function and the germ-free mouse-based simple pharmacokinetics of 3-O-acyl-CAs.
Fig. 5: The effects of C. minuta on HFD-induced intestinal FxrΔIE mice and their wild-type counterparts (Fxrfl/fl).
Fig. 6: The distribution and concentration of 4 newly identified 3-O-acyl-CAs and 12 common BAs in the faeces of the T2D cohort (n = 46 biologically independent individuals).

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Data availability

The datasets generated in this study were deposited in NCBI under Bioproject PRJNA834918. The accession number of the C. minuta genome is JAMBPM000000000. The accession number of the 16S rDNA amplicon data is SRR26844427. The output of the quantitative metabolomics is available in Supplementary Table 15. The seven publicly available datasets used for the identification of species depleted in metabolic disease cohorts are numbered as MD_1 to MD_7, with accession numbers of PRJEB4336 (phenotype: obesity and health), PRJEB12357 (phenotype: obesity and health), PRJEB12123 (phenotype: obesity and health), PRJEB21528 (phenotype: CVD and health), PRJNA422434 (phenotype: type 2 diabetes and health), PRJEB1786 (phenotype: type 2 diabetes and health) and PRJNA373901 (phenotype: NAFLD and health), respectively. Source data are provided with this paper.

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Acknowledgements

This work was supported financially by the National Key Research and Development Program of China and The National Science Fund for Distinguished Young Scholars (2021YFA0717002, 2022YFA1304103, 31925021, 2019YFA0905601 and 2018YFA0800701).

Author information

Author notes

  1. These authors contributed equally: Chang Liu, Meng-Xuan Du, Li-Sheng Xie.

Authors and Affiliations

  1. State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China

    Chang Liu, Meng-Xuan Du, Xin-Wei Sun, Yu Jiang, Min-Zhi Jiang, Hao-Jie Huang, Dalei Wu, Lu-Shan Wang & Shuang-Jiang Liu

  2. State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China

    Chang Liu & Shuang-Jiang Liu

  3. College of Life Science, Hebei University, Baoding, P. R. China

    Li-Sheng Xie

  4. State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, P. R. China

    Wen-Zhao Wang, Bao-Song Chen, Shan-Shan Qiao & Hong-Wei Liu

  5. Department of Physiology and Pathophysiology, School of Basic Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, P. R. China

    Chu-Yu Yun, Xi Luo, Kai Wang & Changtao Jiang

  6. The Second Hospital of Shandong University, Jinan, P. R. China

    Min Sun & Bao-Juan Cui

  7. Shimadzu (China) Co, Beijing, P. R. China

    Shu-Ping Qu & Chang-Kun Li

  8. Center of Basic Medical Research, Institute of Medical Innovation and Research, Third Hospital, Peking University, Beijing, P. R. China

    Changtao Jiang

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  1. Chang Liu
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Contributions

C.L. performed the in silico analysis. M.-X.D., L.-S.X., Y.J., C.-Y.Y., M.-Z.J. and S.-S.Q. performed the animal trials and related tests. C.L., M.-X.D., L.-S.X., X.-W.S. and L.-S.W. performed the in vitro experiments. C.L., B.-S.C. and W.-Z.W. characterized the new bile acids. C.L., X.L., K.W., Y.J. and D.W. performed the cell experiments. M.S., B.-J.C., X.-W.S. and H.-J.H. performed the cohort experiments; W.-Z.W, S.-P.Q. and C.-K.L. performed the LC–MS analysis. S.-J.L. and C.L. designed the experiments. S.-J.L., H.-W.L. and C.J. supervised and directed this project. C.L., M.-X.D., L.-S.X. and S.-J.L. analysed the data and wrote the paper. All authors commented on the paper.

Corresponding authors

Correspondence to Changtao Jiang, Hong-Wei Liu or Shuang-Jiang Liu.

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Extended data

Extended Data Fig. 1 The LC-MS/MS spectra of the acylated cholic acid derivates.

a, The m/z size of characteristic product ion and the collision-induced dissociation (CID) energy was illustrated in the panels. b, Extracted ion chromatogram of four new BA compounds (marked as 1, 2, 3, 4 in the panel) produced by C. minuta cells during in-vitro transformation (CM culture) and the retention time alignments with standards of 3’-Acetylcholic acid (Ac-CA, m/z -H: 449.2909), 3’-Propionylcholic acid (Prp-CA, m/z -H: 463.3065), 3’-Butyrylcholic acid (Buty-CA, m/z -H: 477.3222) and 3’-Valerylcholic acid (Val-CA, m/z -H: 491.3378), which were determined by nuclear magnetic resonance (See Supplementary Information Data for more information about NMR analysis). c, Comparison of high-resolution primary mass spectra of four new BAs in C. minuta culture with standards. The formula, calculated mass, measured accurate mass of the standard and culture sample, the mass error in ppm and MS/MS fragmentation similarity score for each new BA were listed in the Supplementary information Table 2.

Extended Data Fig. 2 The LC-MS spectra displaying that the consumption of CA and the production of 4 unknown CA derivates by in vitro C. minuta biotransformation assay.

a and b, The TIC scan and EIC scan results for the broth of C. minuta transformation at 0 hour (a) and 24 hour (b) in the absence of SCFA mixture in the MMGMB media. c and d, The TIC scan and EIC scan results for the broth of C. minuta transformation at 0 hour (c) and 24 hour (d) in the presence of 1 mM SCFA mixture in the MMGMB media. The peak aera for CA (EIC = 407.3 m/z) and four known derivates (EIC = 449.3, 463.3, 477.3 and 491.3, respectively) were marked in the panels, and was used for calculation of CA transformation rate.

Extended Data Fig. 3 The in-vitro biotransformation activity of C. minuta.

a, The production of SCFAs during in vitro cultivation; STD SCFA: standard of SCFAs mixture (1 mM); CM culture: C. minuta cultivated in mGAM liquid media for 24 hours. The peak aera of each kind of SCFA were listed in the Supplementary Information Table 3. b, The diagram displaying the generation of 3-O-acyl-CAs catalyzed by C. minuta cells, cell lysates and crude proteins with different substrates.

Extended Data Fig. 4 The effects of C. minuta on DIO mice.

a, The ileal leptin; b, Plasma low density lipoprotein cholesterol (LDL); c, Liver’s index; d, Plasma aspartate amino transferase (AST); e, Plasma alanine aminotransferase (ALT); f, Hepatic aspartate amino transferase (AST); g, Hepatic alanine aminotransferase (ALT); h, The Plasma lipopolysaccharide (LPS); i, Ileum glucagon-like peptide 1 (GLP-1); j, Colonic GLP-1; k, The quantification of bile acids in ileal contents; l, The transcription level of bile acid receptor genes in ileum; m, The transcription level of bile acid receptor genes in colon; n, The transcription level of genes involved in hepatic circadian clock; o, The transcription level of bile acid related genes in liver. For panel k - o, the group names were marked with different color bars in the panel. DIO_CK group: DIO mice were fed with HFD and daily administrated with PBS buffer, n = 5 biologically independent samples; DIO_ND group: DIO mice (purchased from vendor) were fed with low fat normal control diet and daily administrated with PBS buffer for 8 weeks, n = 5 biologically independent samples; C57BL/6J group: normal C57BL/6J mice were fed with normal chow diet and daily administrated with PBS buffer, n = 5 biologically independent samples; DIO_CM group: DIO mice were fed with HFD and daily administrated with C. minuta cells (5*108 CFU), n = 10 biologically independent samples. For panel a, c, d, e, h, i and j, one-Way ANOVA test followed by Dunnett’s multiple comparisons test was performed for statistical analysis of difference between DIO_CK (the control group) and the other groups; For panel b, f, g, l, m, n and o, Kruskal-Wallis test followed by Dunn’s multiple comparisons test was performed for statistical analysis of difference between DIO_CK (the control group) and the other groups. Symbols: **** indicates P value < 0.0001, *** indicates P value < 0.001, ** indicates P value < 0.01, * indicates P value < 0.05. Data were shown as the mean ± SEM unless otherwise indicated.

Source data

Extended Data Fig. 5 The effects of C. minuta on host metabolism and metabolically-important hormones in DIO mice.

a, The averaged food consumption of each mouse per day; b, The changes of body weight during 7-week treatment; c, Free-diet blood glucose; d, Fasted-diet blood glucose; e and f, Blood glucose profile(e) and the AOC (f) calculated during the oral glucose tolerance test (OGTT); g and h, Blood glucose profile (g) and the aera of the curve (AOC) (h) calculated during the insulin tolerance test (ITT); i, Plasma triglycerides (TG) j, Plasma total cholesterol (TCHO); k, Active GLP-1 stimulus-secretion test; l, Serum insulin secretion test; m, Plasma glucagon; n, Glucose dependent insulin stimulating peptide (GIP); o, Plasma leptin; p, Plasma ghrelin. The physiological and biochemical indexes in panel c-l were measured using venous blood collected before mouse execution while the others were measured after the end-point execution and sampling of mice after 7-week treatments. DIO_CKrepeat group: DIO mice fed with HFD and daily administrated with PBS buffer for 7 weeks, n = 6 biologically independent samples; DIO_CMrepeat group: DIO mice fed with HFD and daily administrated with C. minuta cells (2*109 CFU) for 7 weeks, n = 6 biologically independent samples. C57BL/6Jrepeat group: normal C57BL/6J mice fed with normal control diet and daily administrated with PBS buffer for 7 weeks, n = 5 biologically independent samples; For panels a, Welch’s ANOVA test followed by two-sided Dunnett’s T3 multiple comparisons test was performed for statistical analysis of difference between DIO_CKrepeat (the control group) and the other groups; For panel b, d, f, g, h, i, j, l, and m, one-Way ANOVA test followed by Dunnett’s multiple comparisons test was performed for statistical analysis of difference between DIO_CKrepeat (the control group) and the other groups; For panel c, e, k, n, o and p, Kruskal-Wallis test followed by Dunn’s multiple comparisons test was performed for statistical analysis of difference between DIO_CKrepeat (the control group) and the other groups. Data were shown as the mean ± SEM unless otherwise indicated.

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Extended Data Fig. 6 The microbiota and metabolome of caecal contents of experimental mice.

a and b, the box-and-whiskers plots displaying alpha diversity with Shannon index (a) and Chao1 index (b); statistical method: two-sided T test/ANOVA; c and d, the pCoA plots displaying the beta diversity; distance method: Bray-Curtis Index, statistical method: ANOSIM; e and f, The histograms displaying the LDA Effect Size (LefSe) analysis results of significantly differed taxonomic compositions at known taxonomic levels (e) and amplicon sequence variant (ASV) level (f); g, The volcano plot displaying the differed metabolite compositions of intestinal contents between DIO_CM and DIO_CK mice; Two-tail T test was used for statistical analysis of the significance of fold changes (FCs). The solid circles were colored by their metabolite categories as listed in the top of the panel; the 25 significantly-changed metabolites between DIO_CM and DIO_CK groups (P value < 0.05) were listed in the panel; h, The bar chart displaying the total concentrations of each chemical class that were significantly changed in panel g; i, The bar chart displaying the concentration of TUDCA, GUDCA and T-βMCA in the caecal contents; j, The correlation network displaying the spearman correlations between the changes of ASVs and gut metabolites; The square nodes represented the significantly changed metabolites in panel g and colored in terms of their chemical class, while the circle nodes represented the significantly changed ASVs listed in panel e; enriched metabolites/ASVs: pink color, reduced metabolites/ASVs: green color; The edge thickness manifested the correlation r values (the minimal cut-off value was 0.7), and the colors displayed the positive (pink) and negative (green) correlations between ASVs and metabolites. n = 5 biologically independent samples for DIO_CK, DIO_ND and C57BL/6J groups; n = 10 biologically independent samples for DIO_CM group. For panel h and i, two-tail T test was performed for statistical analysis of difference between DIO_CK and DIO_CM group; Symbols: **** indicates P value < 0.0001, *** indicates P value < 0.001, ** indicates P value < 0.01, * indicates P value < 0.05. Data were shown as the mean ± SEM unless otherwise indicated.

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Extended Data Fig. 7 The multiple reaction monitoring (MRM) chromatograms of 3’-Acetylcholic acid (Ac-CA, a), 3’-Propionylcholic acid (Prp-CA, b), 3’-Butyrylcholic acid (Buty-CA, c) and 3’-Valerylcholic acid (Val-CA, d) and the retention time alignments of the standard (5 mg/ml), a representative mouse ileal content sample and a representative human fecal sample.

The high-resolution primary mass spectrum of each parent ion was provided at the top left corner in each panel. The accurate mass and mass error (ppm) of four compounds in the standard and each measured sample were listed in the Supplementary information Table 6. See Supplementary information Table 7 and Supplementary Information Table 13 for more detailed parameters and conditions used in the MRM methods.

Extended Data Fig. 8 The effects of 3-O-acyl-CAs on cell cultures.

a, The Dual-luciferase assay exhibiting the activation effect of FXR by 3-O-acyl-CAs, n = 4 biologically independent samples; b, The evaluation of cytotoxin of Ac-CA to Caco-2 cells with cell counting kit-8, n = 3 biologically independent samples; c, The evaluation of cytotoxin of Buty-CA to HEK293 cells with cell counting kit-8, n = 3 biologically independent samples; d, The evaluation of cytotoxin of Ac-CA to Caco-2 cells with cell counting kit-8, n = 3 biologically independent samples; e, The evaluation of cytotoxin of Buty-CA to Caco-2 cells with cell counting kit-8, n = 3 biologically independent samples; f, the dose–response inhibition of FXR by TβMCA, n = 3 biologically independent samples; g, the half maximal inhibitory concentrations (IC50) of TβMCA to the FXR; h, The Dual-luciferase assay exhibiting the effect of TGR5, n = 4 biologically independent samples; i and j, the distribution of CAs in germfree mice gavaged with 10 mg/kg body weight buty-CAs (g, n = 3 biologically independent samples) and in conventional C57BL/6J (h, n = 5 biologically independent samples). For panel a to f and h, one-Way ANOVA test followed by Dunnett’s multiple comparisons test was performed for statistical analysis of difference between control group (or 0 time point group) and the other groups; For panel i, Kruskal-Wallis test followed by Dunn’s multiple comparisons test was performed for statistical analysis of difference between the control group or 0 h group and the other groups. Symbols: **** indicates P value < 0.0001, *** indicates P value < 0.001, ** indicates P value < 0.01, * indicates P value < 0.05. Not significant groups were not marked in the panels. Data were shown as the mean ± SEM unless otherwise indicated.

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Extended Data Fig. 9 The distribution of bile acids in germ-free mice gavaged with 10 mg/kg body weight buty-CAs after different time period.

The time point that the mice were sacrificed for analysis was marked in the panels with different colors of bars; n = 3 biologically independent samples; Kruskal-Wallis test followed by Dunn’s multiple comparisons test was performed for statistical analysis of difference between the control group or 0 h group and the other groups. Not significant groups were not marked in the panels. Data were shown as the mean ± SEM unless otherwise indicated.

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Extended Data Table 1 The representative gut microbes for screening of BA transformation activity
Full size table

Supplementary information

Supplementary Information

Supplemenetary Figs. 1 and 2, data and Tables 1–15. Supplementary Fig. 1. The taxonomic diversity of the 175 species that were negatively associated with metabolic diseases. a, The phylogenetic tree of the 175 gut microbial species that were depleted in at least one of the investigated seven cohort studies with metabolic diseases and their distributions in all the assessed gut metagenomic samples. The phylogenetic tree was constructed using the 16S rRNA gene sequences by the neighbour-joining method with 1,000 bootstraps. b, A heatmap displaying the LDA score (log10) of 175 species enriched in the healthy cohort compared with diseased counterparts for each cohort study (MD_1 to MD_7) based on LEfSe analysis. The 87 species for which we did not have cultivable representatives are marked as ‘NA’ in front of their Latin name. The colour depth of the heatmap indicates the LDA score (log10) of each species for study MD_1 to MD_7. The accession number of each study is available in Data Availability. Supplementary Fig. 2. LC–MS spectra showing that the C. minuta catalyse diverse BA compounds into corresponding acylation conjugates. a–g, C. minuta-mediated acylation of CA (a), CCA (b), TCA (c), CDCA (d), GCDCA (e), TCDCA (f) and DCA (g). The extracted-ion chromatogram scan-based peak area and m/z size of the BAs and their acylated derivates was marked in the panels. Supplementary data. The results of nuclear magnetic resonance-based characterization of 3-O-acyl-CAs.

Reporting Summary

41564_2023_1570_MOESM3_ESM.xlsx

Supplementary Table 1. The representative gut microbes for screening of BA transformation activity. Supplementary Table 2. The accurate mass and errors of the standards and metabolites in samples. Supplementary Table 3. The production of SCFAs during in vitro cultivation. Supplementary Table 4. The information of proteins in the purified catalytic protein components. Supplementary Table 5. The abundance and taxonomy table of ASVs. The reads abundance for each sample were nomolized to the minimum size of 106,179. Supplementary Table 6. The accurate mass and mass error (ppm) of four compounds in the standard and each measured sample. Supplementary Table 7. The MRM-based quantification of bile acids in vivo. Supplementary Table 8. The basic information of faecal donors in the cohort. Supplementary Table 9. The commercial kits used in this study. Supplementary Table 10. Primers and annealing temperatures of the real time qPCR assays. Supplementary Table 11. Basic information of bile acids detected by LC–MS. Supplementary Table 12. The gradient elution pattern used for LC–MS analysis in this study. Supplementary Table 13. MRM method characteristics and validation parameters for the quantification of bile acids in liver tissue by LC–MS/MS. Supplementary Table 14. The accessions and group of each valid runs used for in silico analysis. Supplementary Table 15. The output of quantitative metabolomics.

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LC–MS/MS spectra without data for Fig. 1d.

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Schematic diagram without data for Fig. 3a.

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Extended Data Fig. 6a–f are the outputs of in silico analysis of 16S rDNA amplicon data. The raw ASV table is given in Supplementary Table 5. Extended Data Fig. 6g–i are the result of metabolomics. The raw data table is provided as Supplementary Table 15

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Liu, C., Du, MX., Xie, LS. et al. Gut commensal Christensenella minuta modulates host metabolism via acylated secondary bile acids. Nat Microbiol 9, 434–450 (2024). https://doi.org/10.1038/s41564-023-01570-0

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